Deadzone Detection in Surveillance Camera Networks
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Solution Overview
Problem
Surveillance camera systems often suffer from deadzones, areas not covered by camera views due to improper installation, camera selection, or obstructions, leading to incomplete security coverage and the need for additional cameras to address these gaps.
Innovation Solution
A method and system that determine deadzones by tracking motion within image data from surveillance cameras, using a mobile user device to define critical paths and collect position information, which is then analyzed to identify areas not captured by any camera, allowing for the mapping and display of deadzones on a floor plan for improved installation and coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional cameras are deployed to eliminate deadzones, then security coverage is improved, but system cost and complexity increase
Solution Approach 1:
The system performs deadzone detection during the installation phase before final camera deployment is completed. By using a mobile device to traverse the premises and detect areas not covered by camera fields of view, installers can identify deadzones upfront and adjust camera positions or add cameras only where necessary, rather than deploying excessive cameras and then trying to optimize coverage later.
Solution Approach 2:
The system uses the installer's own mobile device (smartphone or tablet) that they already carry, rather than requiring specialized detection equipment. The mobile device's camera and sensors are utilized to detect deadzones, making the installer self-sufficient for the detection task without needing additional specialized tools or equipment.
2Reliability
If camera positions are adjusted to eliminate deadzones, then coverage is improved, but installation time and effort increase
Solution Approach 1:
The system provides real-time feedback to the installer by displaying detected deadzones on a map or floor plan view on the mobile device. This immediate visual feedback allows the installer to see exactly which areas are not covered and make targeted adjustments to camera positions, rather than having to manually check coverage throughout the entire premises repeatedly during installation.
Solution Approach 2:
The system replaces manual visual inspection and trial-and-error camera positioning with automated digital detection. The mobile device automatically analyzes camera fields of view and identifies deadzones through software processing, substituting the mechanical process of manual coverage verification with an automated computational approach that is faster and more accurate.
3Productivity
If deadzones are detected during installation, then camera placement efficiency is improved, but detection capability is initially lacking
Solution Approach 1:
The system makes the mobile device serve multiple functions: it acts as both the detection instrument for identifying deadzones and the display device for visualizing the results. The same device that the installer uses for general communication and information access is also utilized for the specialized task of deadzone detection, eliminating the need for separate specialized detection equipment.
Solution Approach 2:
The system introduces a software intermediary layer that processes camera field of view data and translates it into visual deadzone maps. This software mediator takes the raw data from camera specifications and mobile device position information, performs the analysis to identify uncovered areas, and presents the results in an easily interpretable visual format on the mobile device screen.
Data Source
AI summary
A system and method for deadzone detection in a surveillance camera network is disclosed. In a preferred embodiment, a mobile user device held by an installer is moved through one or more critical paths within the premises while surveillance cameras of the network are capturing image data of the premises. An analytics system then tracks the installer/user device through the image data over the time interval for the critical path definition, and locates deadzones based on position information of the premises along the critical path and absence of installer/user device in the image data over the time interval. In another embodiment, an analytics system identifies individuals within image data captured from the cameras, tracks movement of the individuals across the fields of view of the cameras represented by the image data, and infers deadzones based on tracking the individuals and deadzone times calculated for each of the individuals.